{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ***Introduction to Radar Using Python and MATLAB***\n",
    "## Andy Harrison - Copyright (C) 2019 Artech House\n",
    "<br/>\n",
    "\n",
    "# Reflection and Transmission\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Referring to Section 2.6, practical radar problems involve waves propagating in bounded regions and interacting with media of differing constitutive parameters.  These media may include the targets of interest to the radar system as well as other regions such as rain, buildings, trees, and birds.  Therefore, it is beneficial to study the reflection and refraction of electromagnetic waves occurring when a wave traveling in a given medium impinges on another medium with a different set of constitutive parameters.\n",
    "\n",
    "The reflection and transmission coefficients for perpendicular polarization are given by (Equations 2.102 and 2.103)\n",
    "\n",
    "\\begin{align}\n",
    "\\Gamma_{{\\scriptstyle TE}} &= \\frac{\\eta_2 \\cos \\theta_i - \\eta_1 \\cos \\theta_t}{\\eta_2 \\cos \\theta_i + \\eta_1 \\cos \\theta_t},\\\\ \\nonumber \\\\\n",
    "\\mathrm{T}_{{\\scriptstyle TE}} &= \\frac{2\\, \\eta_2 \\cos \\theta_i}{\\eta_2 \\cos \\theta_i + \\eta_1 \\cos \\theta_t}\\nonumber\n",
    "\\end{align}\n",
    "\n",
    "The reflection and transmission coefficients for parallel polarization are given by (Equations 2.114 and 2.115)\n",
    "\n",
    "\\begin{align}\n",
    "\\Gamma_{{\\scriptstyle TM}} &= \\frac{\\eta_2 \\cos \\theta_t - \\eta_1 \\cos \\theta_i}{\\eta_2 \\cos \\theta_t + \\eta_1 \\cos \\theta_i} \\label{eq:parallel_reflection_coefficient},\\\\ \\nonumber \\\\\n",
    "\\mathrm{T}_{{\\scriptstyle TM}} &= \\frac{2 \\, \\eta_2 \\cos \\theta_i}{\\eta_2 \\cos \\theta_t + \\eta_1 \\cos \\theta_i}.\n",
    "\\end{align}\n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Begin by getting library path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import lib_path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set the operating frequency (Hz), th relative permittivity, the relative permeability, and the conductivity (S/m) for the different regions using the `array` routine from `scipy`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy import array\n",
    "\n",
    "frequency = 300e6\n",
    "\n",
    "relative_permittivity = array([1.3, 2.8])\n",
    "\n",
    "relative_permeability = array([1.0, 1.0])\n",
    "\n",
    "conductivity = array([0.01, 0.01])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up the keyword args"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "kwargs = {'frequency':              frequency,\n",
    "\n",
    "          'relative_permittivity':  relative_permittivity,\n",
    "\n",
    "          'relative_permeability':  relative_permeability,\n",
    "\n",
    "          'conductivity':           conductivity}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculate the critical angle and Brewster angle using the `plane_waves` routine from `wave_propagation`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Critical Angle 81.1+51.0j\n",
      "Brewster Angle 54.8+3.0j\n"
     ]
    }
   ],
   "source": [
    "from Libs.wave_propagation import plane_waves\n",
    "\n",
    "critical_angle = plane_waves.critical_angle(**kwargs)\n",
    "\n",
    "brewster_angle = plane_waves.brewster_angle(**kwargs)\n",
    "\n",
    "\n",
    "# Display the results\n",
    "\n",
    "print('Critical Angle {:.1f}'.format(critical_angle))\n",
    "\n",
    "print('Brewster Angle {:.1f}'.format(brewster_angle))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set the incident angles using the `linspace` routine from `scipy`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numpy import linspace\n",
    "\n",
    "from scipy.constants import pi\n",
    "\n",
    "incident_angle = linspace(0., 0.5 * pi, 1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up the keyword args"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "kwargs = {'frequency': frequency,\n",
    "\n",
    "          'incident_angle': incident_angle,\n",
    "\n",
    "          'relative_permittivity': relative_permittivity,\n",
    "\n",
    "          'relative_permeability': relative_permeability,\n",
    "\n",
    "          'conductivity': conductivity}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculate the reflection and transmission coefficients using the `plane_waves` routines from `wave_propagation`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "reflection_coefficient_te, transmission_coefficient_te, reflection_coefficient_tm, transmission_coefficient_tm = plane_waves.reflection_transmission(**kwargs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Display the reflection and transmission coefficients using the `matplotlib` routines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "\n",
    "from numpy import degrees\n",
    "\n",
    "\n",
    "# Set the figure size\n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = (15, 10)\n",
    "\n",
    "# Set up the axes\n",
    "\n",
    "fig, axes1 = plt.subplots()\n",
    "\n",
    "axes2 = axes1.twinx()\n",
    "\n",
    "\n",
    "\n",
    "# Display the reflection coefficients\n",
    "\n",
    "axes1.plot(degrees(incident_angle), abs(reflection_coefficient_te), 'b', label='|$\\Gamma_{TE}$|')\n",
    "\n",
    "axes1.plot(degrees(incident_angle), abs(reflection_coefficient_tm), 'b--', label='|$\\Gamma_{TM}$|')\n",
    "\n",
    "\n",
    "\n",
    "# Display the transmission coefficients\n",
    "\n",
    "axes2.plot(degrees(incident_angle), abs(transmission_coefficient_te), 'r', label='|$T_{TE}$|')\n",
    "\n",
    "axes2.plot(degrees(incident_angle), abs(transmission_coefficient_tm), 'r--', label='|$T_{TM}$|')\n",
    "\n",
    "\n",
    "\n",
    "# Set the plot title and labels\n",
    "\n",
    "axes1.set_title('Plane Wave Reflection and Transmission', size=14)\n",
    "\n",
    "axes1.set_xlabel('Incident Angle (degrees)', size=12)\n",
    "\n",
    "axes1.set_ylabel('|Reflection Coefficient|', size=12)\n",
    "\n",
    "axes2.set_ylabel('|Transmission Coefficient|', size=12)\n",
    "\n",
    "\n",
    "\n",
    "# Set the tick label size\n",
    "\n",
    "axes1.tick_params(labelsize=12)\n",
    "\n",
    "axes2.tick_params(labelsize=12)\n",
    "\n",
    "\n",
    "\n",
    "# Set the legend\n",
    "\n",
    "axes1.legend(loc='upper right', prop={'size': 10})\n",
    "\n",
    "axes2.legend(loc='upper left', prop={'size': 10})\n",
    "\n",
    "\n",
    "\n",
    "# Turn on the grid\n",
    "\n",
    "axes1.grid(linestyle=':', linewidth=0.5)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
